Data-Efficient Machine Learning

Speaker:  Houbing Song – Baltimore, MD, United States
Topic(s):  Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing


Most research on machine learning has focused on learning from massive amounts of data resulting in large advancements in machine learning capabilities and applications.  However, many domains lack access to the large, high-quality, supervised data that is required and therefore are unable to fully take advantage of these data-intense learning techniques.  This necessitates new data-efficient learning techniques that can learn in complex domains without the need for large quantities of supervised data. In this lecture, I will provide a comprehensive survey of existing literature in the area of data-efficient machine learning, identify the challenges, and evaluate the trends. I will also introduce our research findings in this area.

About this Lecture

Number of Slides:  45
Duration:  60 minutes
Languages Available:  English
Last Updated: 

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